The circular conversation about robots taking all the jobs rumbles on. In some industries however we see the dawning realisation that automation is not occupation-focussed, but task focussed, and the composition of tasks dictates how fast a role will be automated.

Although automating basic tasks seems attractive at first, a healthy dose of realism is needed. Investment in robots and AI is still high-cost, high-risk at this point. There are still many places where the advantage of humans being low-cost, low-risk outweighs the investment need. We need to see a robotic version of Moore’s Law to take place before we see any big movement towards full automation of knowledge work – but it is coming.

Organisations starting to consider knowledge work automation tend to start by addressing highly repetitive, low-value tasks. Some of these low-value tasks absolutely need to be automated out of the hands of humans, but there is another lens through which to view this trend.

When we first join the workforce, or change career paths, we learn the ropes through undertaking these basic, repetitive tasks. They help us understand how services and processes work and our role in delivering them. So what happens when we have automated these tasks out of existence? How do we continue to bring new people into the workforce, and teach them their trade? Do organisations have a social duty to be ‘for humans’ and their future at work?

Government policy is firmly focussed on investing more in education and training. Although the principle of investing more in education, skills and re-training seems widely accepted, I have lingering doubts as to how re-training can help employees stay one step ahead of the robots. If the tasks that teach you the ropes after re-training have already been automated, how is it helping?

We can count on a heavy dose of organisational inertia preserving these tasks and roles for now. We have time to be more radical, to create a more positive outlook for the workforce of the future. Large organisations are not pushing as hard at the automation topic as you may believe when reading the news. We are still a long way from a general AI that can perform many tasks, everything is still hand-crafted, specialised AI, and therefore complex and expensive.

Organisations are constantly searching for digitally-savvy, young talent to provide a much needed skills boost. Young people may also be better suited to learning new things, but without a place to develop and practice those skills they may well choose to re-think their whole approach to the future of work.